Best Validation check number for MATLAB neural network

2 次查看(过去 30 天)
I'm using 10-fold cross validation and patternent function for a binary classification problem in MATLAB. When I see neural network result window, in all trainings of neural network ( 80% training , 10% validation and 10% test with sample size 200~600 ) Early stopping is stopping my training process in iteration between 20~40. As you know the default value is maximum 6. What should i do about this problem? Should i increase maximum number of early stopping iteration checks?
Thanks.

采纳的回答

Greg Heath
Greg Heath 2014-9-5
编辑:Greg Heath 2014-9-5
That is not necessarily a problem.
What error rates are you getting as you vary the number, H, of hidden nodes and sets of random initial weights?
I typically look at Ntrials = 10 different initial weight initializations for each candidate value of Hmin:dH:Hmax (numH~10).
Search in NEWSGROUP and ANSWERS
greg patternet Ntrials
Hope this helps.
Thank you for formally accepting my answer
Greg

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by